000147171 001__ 147171
000147171 005__ 20241212141913.0
000147171 0247_ $$2doi$$a10.26754/jjii3a.202410613
000147171 0248_ $$2sideral$$a140850
000147171 037__ $$aART-2024-140850
000147171 041__ $$aeng
000147171 100__ $$aRamón Júlvez, Ubaldo$$uUniversidad de Zaragoza
000147171 245__ $$aEPDIFF-JF-NET: Adjoint Jacobi Fields for Diffeomorphic Registration Networks
000147171 260__ $$c2024
000147171 5060_ $$aAccess copy available to the general public$$fUnrestricted
000147171 5203_ $$aThis paper presents a deep learning unsupervisedapproach for diffeomorphic image registrationcalled EPDiff-JF-Net. We propose a novel paralleltransport layer to compute the gradients necessaryfor training with adjoint Jacobi fields. We test ourmethod on two independent brain MRI datasets andobtain state-of-the-art results.
000147171 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T64-20R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-104358RB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2022-138703OB-I00
000147171 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttp://creativecommons.org/licenses/by-nc/3.0/es/
000147171 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000147171 700__ $$0(orcid)0000-0003-1270-5852$$aHernández Giménez, Mónica$$uUniversidad de Zaragoza
000147171 700__ $$0(orcid)0000-0002-9109-5337$$aMayordomo Cámara, Elvira$$uUniversidad de Zaragoza
000147171 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000147171 773__ $$g12 (2024), [2 pp.]$$pJorn. jóvenes investig. I3A$$tJornada de jóvenes investigadores del I3A$$x2341-4790
000147171 8564_ $$s260231$$uhttps://zaguan.unizar.es/record/147171/files/texto_completo.pdf$$yVersión publicada
000147171 8564_ $$s2873672$$uhttps://zaguan.unizar.es/record/147171/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000147171 909CO $$ooai:zaguan.unizar.es:147171$$particulos$$pdriver
000147171 951__ $$a2024-12-12-12:44:20
000147171 980__ $$aARTICLE